Abstract — Motivated by control applications over lossy packet networks, this paper considers the Linear Quadratic Gaussian (LQG) optimal control problem in the discrete time setting and when packet losses may occur between the sensors and the estimation-control unit and between the latter

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Building a more sustainable sensor network via protocol innovation

Abstract—We investigate control of a non-linear process when communication and processing capabilities are limited. The sen-sor communicates with the controller node through an erasure channel which introduces independent and identically distributed (i.i.d.) packet dropouts. Processor availability

Abstract We provide an overview and some recent results on real-time communication and control over Gaussian channels. In particular, the problem of remote stabilization of linear systems driven by Gaussian noise over Gaussian relay channels is considered. Necessary and sufficient conditions

in partial ful2llment of the requirements for the degree of

Public reporting burden for this collection of Information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send

April 29, 2011Für UnsShe had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it Lewis CarrollThe following document, written under the supervision of Dr. reviewed by:

First and foremost, I would like to thank my advisor, Prof. Jennifer E. Michaels. I am most appreciative of your guidance over the last four years, from the basics of elastic waves to both short- and long-term career advice. I have grown a tremendous amount, both profes-sionally and personally, and am deeply grateful for your mentorship, patience, and support. I would also like to thank my Ph.D. committee for their valuable insight and sugges-

frameworks. Exploiting the parametric nature of the radar problem, these techniques allow significant reduction in sampling rate, implying potential power savings, while maintaining the systems estimation capabilities at sufficiently high signal-to-noise ratios. Here we present for the first time a design